Dynamic programming is a problem-solving technique used in computer science and mathematics to break down complex problems into simpler subproblems. It is particularly useful for optimization problems, where the goal is to find the best solution among many possible options. By storing the results of these subproblems, dynamic programming avoids redundant calculations, making the overall process more efficient. This method is often applied in various fields, such as algorithm design, operations research, and bioinformatics. A classic example of dynamic programming is the Fibonacci sequence, where each number is the sum of the two preceding ones. By storing previously calculated values, we can quickly compute larger Fibonacci numbers without unnecessary repetition.