I was reading the Naive Bayes article on Wikipedia and I read that, In Naive Bayes, the naive assumption that Naive Bayes make is "each feature is conditionally independent of every other feature, given the category Ck". So, I was wondering if 'Conditional Independence' means there should be no multicollinearity among features?
No, it does not imply lack of multicolineaity. Suppose $X$ and $Y$ are normal with variance 0.001, and have mean $\mu = 100$ if $Z = 1$ and mean $\mu = -100$ if $Z = 0$, but are conditionally independent given $Z$. There is still extreme multicolineairty here, with the correlation being very close to $1$.