A neighborhood of point x is an open set containing x. Neighborhoods capture the intuition of 'regions around x.' Every topological space is determined by the neighborhood structure: two topologies are equal iff they assign the same neighborhoods to every point. Neighborhoods enable local analysis of topological spaces.
From your study of open sets in topology, you know that a topology on a space X is defined by specifying which subsets are "open," subject to the axioms (X and ∅ are open; arbitrary unions of open sets are open; finite intersections of open sets are open). A neighborhood of a point x is simply any open set that contains x. This seemingly minor repackaging — going from "open sets of the space" to "open sets around a point" — is a conceptual shift from global to local analysis.
Why is the local perspective useful? Because most of the properties we care about in analysis and topology are local: continuity, convergence, and limit points all depend on what happens near a point, not on the entire space at once. A function f: X → Y is continuous at x if and only if the preimage of every neighborhood of f(x) is a neighborhood of x. A sequence (xₙ) converges to x if and only if every neighborhood of x contains all but finitely many terms of the sequence. In both cases, the question reduces to: what sets contain x? The neighborhood concept focuses your attention precisely there.
The collection of all neighborhoods of x is called the neighborhood filter at x. Filters are closed under supersets (if U is a neighborhood of x and U ⊆ V, then V is a neighborhood of x) and finite intersections (the intersection of two neighborhoods of x is a neighborhood of x). These closure properties make the neighborhood filter a clean algebraic object. More importantly, the topology is completely determined by its neighborhood structure: a set U is open if and only if it is a neighborhood of every point it contains. You can verify this directly — if every point x in U has a neighborhood Nₓ ⊆ U, then U = ⋃ₓ Nₓ, a union of open sets, hence open.
The practical payoff is that local analysis decomposes complex global questions into manageable point-by-point questions. Rather than asking "is this map continuous everywhere?" you ask "does the preimage of each neighborhood at f(x) contain a neighborhood of x?" at each x. This decomposition is why neighborhoods are the natural language for the concepts you'll encounter next: limit points (which ask whether every neighborhood of x meets a set A) and convergence in topology (which asks whether sequences eventually land in every neighborhood). The neighborhood perspective is not just convenient notation — it is the right level of abstraction for doing local topology.