This lecture covers the Nearest Neighbor search algorithm, focusing on the Johnson-Lindenstrauss lemma for dimensionality reduction. The instructor explains the concept of Nearest Neighbor search and the importance of the Johnson-Lindenstrauss lemma in reducing dimensionality. The lecture discusses the process of preprocessing data to improve search efficiency and the use of locality-sensitive hashing for approximate nearest neighbor search. Various techniques, such as hash families and sensitive hashing, are explored to optimize the search process.