A greedy algorithm iterates through the problem space taking the optimal solution "so far" until it reaches the end.

Greedy approaches are great because they are fast (usually one pass through the input).

Ask yourself, suppose we could come up with the answer for one pass through the input by updating the 'best answer so far' as we went. What additional values would we need to keep updated as we looked at each item in our set, in order to be able to update the 'best answer so far'?