Solution
Greedy algorithms work by making a sequence of choices, each of which is locally optimal, with the hope that these choices will lead to a globally optimal solution. The greedy approach is often used when a problem has an optimal substructure, meaning that the optimal solution can be constructed from optimal solutions to its sub problems.
A classic example is the Coin Change problem: choose the largest denomination coin that does not exceed the remaining amount, subtract that value, and repeat until the desired amount is achieved. Greedy algorithms are often faster and easier to implement, but they do not always guarantee the optimal solution.