[D] Why RLHF instead of direct ranking loss?

This may be basic question for some one but it bothers me for a while. For the instructgpt or whatever following model with alignment, RLHF seems to be the standards. We get human feedback and train a reward model, then we use rl to further finetune the model. However, why not directly use human feedback to finetune with a simple ranking loss(e.g pairwise loss)?
What might be the best advantage for RLHF?

alignment basic feedback human human feedback instructgpt loss machinelearning ranking rlhf standards