Algorithm A has complexity like AO(n) and algorithm B goes like BO(n^2) (just made-up examples). So one would say that A is better. But the constant A happens to be very large, so that, until n becomes very large, B is actually faster, because the constant B is so much smaller. So conventional analysis would say that A is better in general, but its actual poor performance is "hiding" in the huge constant A, and is worse than B in real situations, where n never gets huge enough for A's complexity advantage to become relevant.
Algorithm A has complexity like AO(n) and algorithm B goes like BO(n^2) (just made-up examples). So one would say that A is better. But the constant A happens to be very large, so that, until n becomes very large, B is actually faster, because the constant B is so much smaller. So conventional analysis would say that A is better in general, but its actual poor performance is "hiding" in the huge constant A, and is worse than B in real situations, where n never gets huge enough for A's complexity advantage to become relevant.