Branch and Bound is an algorithmic technique used for solving optimization problems, particularly in operations research and computer science. It systematically explores the solution space by dividing it into smaller subproblems, or "branches," and evaluates their potential to find the best solution. The method uses a bounding function to eliminate subproblems that cannot yield better solutions than the current best. This helps reduce the number of solutions to consider, making the process more efficient. Branch and Bound is commonly applied in problems like integer programming and combinatorial optimization.