O(2n) Represents exponential time complexity, typical of algorithms that explore all possible combinations or subsets of elements, such as brute-force approaches to certain problems like the subset sum problem or the traveling salesman problem. Exponential algorithms grow exponentially with the input size. These algorithms are significantly less efficient than logarithmic, linear, or constant time complexities. They often become impractical for large input sizes due to their rapid growth in runtime.