Randomized quicksort is a sorting algorithm that improves the efficiency of the traditional quicksort by randomly selecting a pivot element from the array. This randomness helps to avoid the worst-case scenarios that can occur with sorted or nearly sorted data, leading to better average performance. The algorithm works by partitioning the array into two sub-arrays: elements less than the pivot and elements greater than the pivot. It then recursively sorts these sub-arrays. The expected time complexity of randomized quicksort is O(n log n), making it a popular choice for sorting large datasets.