Motivated by the attractive features of robust priors and the MML estimators, we develop Bayesian estimators for the location parameter of a family which represents a very wide class of symmetric location-scale distributions ranging from Cauchy to normal distributions. We show that the new estimators are clearly superior to those obtained earlier by other authors. The proposed method can also be extended to asymmetric location-scale distributions. That will form Part II of this work.