Sagemaker reporting SSLError while trying to predict

My team followed a tutorial on how to set K-Means model for prediction: https://sagemaker-examples.readthedocs.io/en/latest/sagemaker-python-sdk/1P_kmeans_highlevel/kmeans_mnist.html After creating the train data, we tried to predict using the following code:

from sagemaker import KMeans

num_clusters = 2
kmeans = KMeans(role=role,
                instance_count=1,
                instance_type='ml.c4.xlarge',
                output_path=<redacted>
                init_method='kmeans++',
                k=num_clusters
               )

kmeans.fit(kmeans.record_set(train_data_scaled.to_numpy().astype('float32')))

kmeans_predictor = kmeans.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')

kmeans_predictor.predict(train_data_scaled.to_numpy().astype('float32'))

Using conda_python3 kernel in Jupyter Notebook.

But we're seeing the following error

SSLError: SSL validation failed for https://runtime.sagemaker.us-east-1.amazonaws.com/endpoints/kmeans-<redacted>/invocations EOF occurred in violation of protocol (_ssl.c:2396)

We didn't do anything to customize the sagemaker endpoint, documentation for KMeans predict method does not seem to have any flag available to ignore ssl validation either.