To oversimplify slightly*, when we talk about lower bounds for
algorithmic problems, we're interested in how the best algorithm
does in the worst case. The best comparison-based sorting
algorithms (e.g., mergesort) use roughly n log n comparisons in the worst
case, so the lower bound for sorting is quoted as Omega(n log n).
Algorithms that are not the best, e.g., bubble sort, may do materially
worse than the best algorithm in the worst case. In the best case, they may
do better than the best algorithm. Neither of these facts is inconsistent
with the lower bound for sorting.
*There may not be one best algorithm.