Tabu Search is an optimization algorithm used to solve complex problems by exploring the solution space. It starts with an initial solution and iteratively moves to neighboring solutions, aiming to improve the objective function. To avoid cycling back to previously visited solutions, it maintains a list of "tabu" solutions that are temporarily forbidden. The algorithm employs strategies like aspiration criteria, which allow for revisiting tabu solutions if they offer a better outcome. Tabu Search is particularly effective for problems like scheduling, routing, and resource allocation, where traditional methods may struggle to find optimal solutions efficiently.