Dynamic Programming is a method for solving complex problems by breaking them down into simpler overlapping subproblems. The approach is applicable when the problem exhibits: (1) Optimal substructure - optimal solution contains optimal solutions to subproblems; (2) Overlapping subproblems - same subproblems are solved multiple times. DP stores solutions to subproblems (memoization) to avoid redundant computation. Key applications include: shortest path problems, resource allocation, inventory management, production planning, and the knapsack problem. The Bellman equation characterizes optimal solutions recursively.