CLT may fail under this condition? CLT says that when sample size n goes to infinity, the sample sum or average curve converges to normal distribution.
My question is: if the sample size goes closer or even equal to the population size, wouldn't the average values cram so closely near the mean, that violate the "bell shape" distribution?


My question is: if the sample size goes closer or even equal to the population size, wouldn't the average values cram so closely near the mean, that violate the "bell shape" distribution?

Indeed, if you sample without repetition from a population, then for $n$ closer to the population size you get a distribution that at some point is exactly equal to the true mean of the population.
But, note that you do not have all conditions that are necessary for the central limit theorem to apply. You need to have the individuals in the sample to be independent. This is not the case when you sample form a finite population without repetition.
