Big O notation measures an algorithm's performance scaling with input size, comparing efficiency between algorithms. Common time complexities: Constant (O(1)), Linear (O(n)), Quadratic (O(n^2)) & Cubic (O(n^3)). Nested loops multiply time complexity!