Dynamic programming is an algorithm design technique for optimization problems that involves breaking down problems into sub-problems and storing solutions to sub-problems in tables to avoid recomputing them. It is used to minimize or maximize problems by combining solutions to sub-problems, with sub-problems potentially sharing sub-sub-problems. Dynamic programming reduces time complexity by increasing space complexity through storing optimal solutions to sub-problems in tables.