最邻近搜索（Nearest Neighbor Search, NNS）又称为“最近点搜索”（Closest point search），是一个在尺度空间中寻找最近点的优化问题。问题描述如下：在尺度空间M中给定一个点集S和一个目标点q ∈ M，在S中找到距离q最近的点。很多情况下，M为多维的欧几里得空间，距离由欧几里得距离或曼哈顿距离决定。

高德纳在《计算机进程设计艺术》（1973）一书的第三章中称之为邮局问题，即居民寻找离自己家最近的邮局。

Nearest neighbor search (NNS), also known as proximity search, similarity search or closest point search, is an optimization problem for finding closest (or most similar) points. Closeness is typically expressed in terms of a dissimilarity function: the less similar the objects, the larger the function values. Formally, the nearest-neighbor (NN) search problem is defined as follows: given a set S of points in a space M and a query point q ∈ M, find the closest point in S to q. Donald Knuth in vol. 3 of The Art of Computer Programming (1973) called it the post-office problem, referring to an application of assigning to a residence the nearest post office. A direct generalization of this problem is a k-NN search, where we need to find the k closest points.