You have cities connected by flights with costs. Find the cheapest route from city src to city dst with at most stops. A stop is an intermediate city between source and destination. This is a constrained shortest path problem. You cannot use standard Bellman-Ford because it finds paths with minimum edges, not constrained stops.
The constraint changes the relaxation logic. At most stops means at most flights (edges). You need to control how many edges are used in the shortest path.