Time complexity of Prim's algorithm
The time complexity is $O(n^2)$ because $O(n\cdot(n-1)) = O(n^2)$

The big-O notation is showing the worst-case performance of one algorithm, it is not showing the exact number of steps the algorithm will make, but only its overall complexity

For example $$O(2n) = O(n)\\O(3n) = O(n)\\O(\frac{n}{2}) = O(n)\\O(2n^2) = O(n^2)$$