Why is recursion beneficial for algorithms like quicksort?

Recursion is particularly beneficial for algorithms like quicksort because it aligns perfectly with the divide-and-conquer strategy. In quicksort, the algorithm works by selecting a 'pivot' element and partitioning the array into two subarrays: elements less than the pivot and elements greater than the pivot. Each of these subarrays can then be sorted independently using the same quicksort algorithm.

This ability to divide the problem into smaller, more manageable problems is central to the recursion process. Each recursive call to quicksort deals with a smaller portion of the original array, simplifying the representation and manipulation of the data. The recursive nature of quicksort enables it to cleanly handle the sorting of these partitions without needing to explicitly manage the state as you would with a loop.

While recursion can simplify code and make it more elegant, it is essential to note that it does not inherently guarantee faster execution, nor does it always use less memory. The memory usage of recursion can sometimes exceed that of an iterative approach due to the call stack storing information for each recursive invocation. Therefore, quicksort's effectiveness and clarity when implemented recursively stem from its alignment with the divide-and-conquer paradigm, making option B the most accurate choice.