Constant time complexity O(1) can be proven as a subset of logarithmic time complexity O(log n) by leveraging the definition of Big-Oh. For any function f in O(1), there exist constants x_0 and M such that f(x) is bounded above by M for all x greater than x_0. By choosing x_1 as the maximum of x_0 and n, it can be shown that f(x) remains less than or equal to M, which is also less than or equal to M log n for sufficiently large n. This demonstrates that O(1) is indeed a subset of O(log n), supporting the broader classification of time complexities. The discussion emphasizes the importance of understanding these relationships within the context of algorithm analysis.