Why is it the Most significant feature from xgboost model is not at all significant when i build a model with same data set but using catboost?
There is no guarantee that you get the same subset of features from any feature selection algorithm. There might be multiple subsets that all perform approximately equally.  For instance, perhaps feature C is highly correlated with feature I.  So, there is no reason to be surprised by what you are observing.  There is no notion of "too low".