refactor: add reasoning behind why we are using K-means to start

Author: sof202

individual_modules/introduction_to_machine_learning/4_unsupervised_learning.ipynb

@@ -31,7 +31,7 @@
     "## K-means clustering\n",
     "\n",
     "* This type of algorithm tries to assign class labels (i.e. generate clusters) from unlabelled data.\n",
-    "* There are many different clustering algorithms, but K-means is a great place to start.\n",
+    "* While there are many types of algorithms that generate clusters, K-means is a great place to start due to its simplicity (much like how we defaulted to linear regressions in previous notebooks).\n",
     "\n",
     "### How does it work?\n",
     "\n",