A k-d tree (short for k-dimensional tree) is a data structure used for organizing points in a k-dimensional space. It is particularly useful for applications like nearest neighbor search and range search. The tree is built by recursively splitting the space into two halves based on the values of the points along different dimensions. Each node in a k-d tree represents a point, and the tree alternates between dimensions as it splits the data. This allows for efficient searching, as the structure can quickly eliminate large portions of the search space, making it faster than a simple list or array for multidimensional data.