Which sorting algorithm is least efficient for large lists?

The least efficient sorting algorithm for large lists is bubble sort. This algorithm operates with a time complexity of O(n^2) in the average and worst-case scenarios, which means the number of comparisons and swaps it needs to make increases dramatically as the number of elements in the list grows.

Bubble sort works by repeatedly passing through the list, comparing adjacent items, and swapping them if they are in the wrong order. This process continues until no swaps are needed, indicating that the list is sorted. Due to its repetitive nature, bubble sort becomes inefficient with larger datasets, as the number of comparisons grows quadratically.

In comparison, while insertion sort and selection sort also have a time complexity of O(n^2), they tend to perform better than bubble sort in practice. Insertion sort is generally more efficient on small or partially sorted datasets, and selection sort makes fewer swaps, which can lead to better performance under certain conditions. Quicksort, on the other hand, is much more efficient for large lists, typically operating in O(n log n) time, making it a favorable choice for sorting larger datasets.