What is the best case time complexity of linear search?

The best case time complexity of linear search is O(1), which means that in the best-case scenario, the item being searched for is located at the very first position of the array or list. This allows for an immediate retrieval of the item without the need to examine any additional elements. The algorithm simply checks the first element and finds a match right away, resulting in a constant time operation regardless of the size of the dataset.

In contrast, linear search has a best case of O(1) and a worst case of O(n), where n is the number of elements in the list, meaning it may need to examine all elements if the target is at the end or not present at all. Meanwhile, O(log n) typically relates to search algorithms that halving the search space each time (like binary search), and O(n^2) refers to algorithms that have nested iterations through the data, which does not apply to linear search.