The Smith-Waterman algorithm is a dynamic programming technique used for local sequence alignment in bioinformatics. It identifies the most similar regions between two sequences, such as DNA, RNA, or proteins, by comparing their characters and scoring matches, mismatches, and gaps. This algorithm is particularly useful for finding conserved sequences in biological data, helping researchers understand evolutionary relationships and functional similarities. By focusing on local alignments, Smith-Waterman can reveal significant similarities that might be missed in global alignment methods, making it a valuable tool in genomics and molecular biology.