Latent Semantic Indexing (LSI) is a natural language processing technique that analyzes relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. It uses singular value decomposition to reduce the dimensionality of the term-document matrix, capturing the underlying structure in the data that reflects semantic relationships.