Which is the most efficient out of Bubble Sort, Selection Sort, Insertion Sort for a identical set of elements?
All elements being the same is equivalent to data being sorted. The class of algorithms you are looking for is adaptive sort, which benefits from presortedness of the input data - this is the justification - since data is already sorted we have to find algorithm that uses this fact. The classic example is the insertion sort, but also Timsort (a variant of natural merge sort) and other exist. All adaptive algorithms should show the best case performance as $\mathcal{O}(N)$, which in case of insertion sort is exactly $N - 1$ comparisons, where $N$ is the length of input data.
There is no need to implement or run those algorithms, it is suficcient to show that part responsible for swapping elements is never executed, show that appropriate conditions are always true (or false depending on code) so analysis is easier.

From the possible algorithms you have provided the best cases are: Bubble sort - $\mathcal{O}(N)$, Selection Sort - $\mathcal{O}(N^2)$ and Insertion Sort - $\mathcal{O}(N)$.