ARIMA models cannot be estimated with the least squares method, because the moving average components are not observable. The technique that is used instead is maximum likelihood, which is certainly more complex, and can sometimes cause numerical errors.

Regardless of whether the data is stationary or not, we will get a resulting model. It is our responsibility to ensure that in that case, the nonstationarity is addressed properly.