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 scoring matches, mismatches, and gaps. This algorithm is particularly useful for finding conserved sequences in biological data. The algorithm works by constructing a scoring matrix based on the sequences being compared. Each cell in the matrix represents a score derived from the best possible alignment up to that point. The final score indicates the highest similarity found, allowing researchers to analyze evolutionary relationships and functional similarities between sequences.