The correct answer is: DFS is space efficient and BFS is time efficient.
DFS (depth-first search) is a recursive algorithm that starts at a given node and explores all of its neighbors before moving on to the next level of the tree. This means that DFS only needs to keep track of the current node and its neighbors, which takes up a relatively small amount of space.
BFS (breadth-first search) is an iterative algorithm that starts at a given node and explores all of its neighbors at the same level before moving on to the next level of the tree. This means that BFS needs to keep track of all of the nodes that it has visited, which can take up a lot of space if the tree is large.
In terms of time complexity, DFS is typically slower than BFS. This is because DFS has to backtrack after it reaches a dead end, while BFS can simply continue exploring the next level of the tree. However, DFS can be faster than BFS if the tree is sparse, since it only needs to explore a fraction of the nodes.
In conclusion, DFS is space efficient and BFS is time efficient. The choice of which algorithm to use depends on the specific application.