Latent Semantic Analysis (LSA) is a natural language processing technique that uncovers the hidden relationships between words in a large corpus by transforming text data into a lower-dimensional space using singular value decomposition. This method captures the underlying semantic structure in the data, allowing for improved information retrieval, text summarization, and semantic similarity assessments.