Describe the concept of space complexity in context with recursive algorithms, particularly highlighting the impact of recursion depth and memoization.

Space complexity measures the memory required by an algorithm. Recursive algorithms’ space complexity is influenced by recursion depth, as each recursive call adds to the call stack. For instance, the naive Fibonacci sequence has O(n) space complexity due to linear recursion depth. Memoization can reduce redundant calls, transforming exponential space complexity to linear by storing intermediate results, optimizing memory usage, and improving time complexity.